Lagrangian Discrete Phase Model Research Articles

Eulerian- lagrangian dense discrete phase model (DDPM) of stenotic LAD coronary arteries in comparison with single phase modeling

In computational fluid dynamic studies related to blood flow, investigating the behavior of blood particles is crucial, especially red blood cells as they constitute a significant proportion of blood particles. Additionally, studying red blood cell movements is necessary, especially in stenotic artery geometries. A new multiphase scheme was utilized to demonstrate the effect of red blood cells on hemodynamics in complex coronary arteries and investigate the consequence of their motion. To investigate the effect of red blood cell movement on flow, the dense discrete phase model (DDPM) was used. This simulation was performed in 3D coronary arteries with different degrees of stenosis, utilizing blood pressure as inlet and outlet boundary conditions while assuming the arterial wall to be rigid. The model prediction shows good agreement with experimental data. Velocity values were comparable in both single-phase and two-phase flow simulations, but the shear stress in two-phase modeling had higher values. In the two-phase DDPM modeling, the recirculation areas indicated a higher probability of atherosclerosis plaque re-formation in the pre-stenosis area compared to the stenosis and post-stenosis areas. The DDPM model was found to be more effective in obtaining shear stress values in the artery. Additionally, this model provides good results compared to the single-phase model in investigating the movement of particles along the artery as well as recirculation areas that lead to the deposition of particles.

A numerical assessment to select the optimal geometry of a specific cyclone separator of wheat flour processing

AbstractIn this study, the effect of the cyclone body height on the flow field within the specific cyclone and also on the performance parameters of the cyclone has been investigated. The five heights of the cyclone as various configurations were I = 600, II = 675, III = 750, IV = 825, and V = 900 mm. A pressure‐based solver was used and the turbulent Reynolds stress model was utilized to simulate the flow. Then, the Lagrangian discrete phase model was used to simulate the solid phase. As the height of the cyclone increases, the pressure drop decreases. Also, the best separation efficiency and the highest particle velocity value were achieved at a height of 750 mm. The maximum values of turbulence intensity, skin friction coefficient, and strain rate were obtained as negative components of cyclone performance at the cyclone body height of 900 mm. The height of 750 mm was recognized as the best height of the cyclone's body.Practical ApplicationsApplying numerical simulation in food processing is a novel method to minimize equipment construction and reach a high‐accuracy design. Computational fluid dynamics can provide an accurate and detailed flow analysis in the cyclone separators utilized in the flour processing plant. The dimensional analysis can help the researchers to achieve the optimum design and enhance the cyclone performance by reducing pressure drop and increasing separation efficiency. Also, the maintenance cost would be significantly reduced due to detecting the critical sections and strengthening them.

Numerical investigation on design parameters of orifice plate for positioning of workpiece in cavitation zone for cavitation machining

ABSTRACT The recent development of non-traditional machining techniques, such as cavitation machining (CM), has been gaining traction amongst researchers due to its sustainable nature. The present research focuses on the use of computational fluid dynamics (CFD) model to predict the location of workpiece in the fluid domain and bubble distribution during CM process. For efficient CM, the correct positioning of a workpiece in cavitation zone is essential, as the implosion of the cavity bubble leads to formation of micro-jet and shock waves for a few milli-to-microseconds generating high temperature and pressure on workpiece. The aim is to harness cavitation phenomena in material processing, particularly by using orifice plates as a common tool to induce hydrodynamic cavitation. To generalise the investigation, the flow simulation through orifice plate with different aspect ratios (l/d) are carried out. For the bubble distribution and their diameters, the Lagrangian discrete phase model (DPM) is used in the downstream side of the flow domain. Using this information, bubble dynamics have also been investigated using the Keller–Miksis (KM) model to compute the implosion time and intensity in the zone. The presented exploration determines the orifice dimensions to optimize implosion intensity, ensuring precise workpiece placement in real-time CM.

Numerical simulation of gas-solid flow in a cyclone separator with additional inlet

In this study, an additional inlet was added to the gas-solid cyclone separator to enhance the separation efficiency. Four different heights were tested, including 0.95D, 1.4D, 1.5D, and 1.95D (D is the diameter of the cylindrical section). The investigation involved two inlet flow conditions: increasing and dividing the inlet flow rate. The finite volume method and Reynolds stress turbulence model were used to solve the averaged Navier–Stokes equations, whereas the Eulerian–Lagrangian approach and discrete phase model (DPM) were applied to track particles with a uniform diameter of 0.5–1.8 microns as the discrete phase. Owing to the low Stokes number and small and low-volume-fraction particles, a one-way coupling method was employed between air and the particles. The addition of an additional inlet reduced the static pressure in the center and downstream areas and increased the reverse flow velocity at the end of the cyclone. The installation of an additional inlet at 0.95D had the most positive effect on the separation efficiency, with an increase of 28.8% in the increasing flow rate case and 19.6% in the dividing flow rate case compared with the cyclone without an additional inlet. Furthermore, the increase in the separation efficiency of the submicron particles was greater than that of the larger particles in both flow distribution cases.

Modeling of Motion of Inclusions in Argon‐Stirred Steel Ladles

A 3D discrete phase model (DPM)‐ and volume of fluid–coupled model is developed to investigate the multiphase flow in a 260 ton argon‐stirred ladle. The flow field and interfacial behavior in the argon‐stirred ladle are accurately predicted. Then, the Lagrangian DPM is used to trace the motion of inclusions in the liquid steel. Residence time maps, which provided the residence time required for inclusions travelling from the bulk liquid steel to the steel–slag interface, are proposed and plotted as functions of inclusion diameter and percentage of inclusions. For inclusions smaller than 10 μm, the average residence time is size‐independent but decreases from 175 to 93 s with an increment in the gas flow rate from 50 to 400 NL min−1. With increasing the inclusion size, the average residence time is dependent on both gas flow rate and inclusion diameter. When the inclusion diameter increases to 1000 μm, the average residence time is almost independent of the gas flow rate. The current model overestimates the inclusion removal rate. However, this overestimation indicates that only appropriately considering the behavior of inclusions at the steel–slag interface can accurately predict the removal of inclusions in argon‐stirred ladles.

Optimize the Operation Parameters in Surging Auxiliary Slag Skimming Process Based on Large Eddy Simulation –Volume of Fluid –Discrete Phase Model Coupled Model

A transient 3D mathematical model is developed to study the surging auxiliary slag skimming process in molten iron ladle. A new mathematical model using the large eddy simulation is built for the gas–metal–slag three‐phase flow in the ladle. The Eulerian volume of fluid model is used for tracking the liquid–slag–air free surfaces, and the Lagrangian discrete phase model is used for describing the bubble movement. The procedure of bubble coming out of the liquid and getting into the air is modeled using a user‐defined function. The results show that optimizing the distance of the lance L and the injection volume Q can better the shape of the slag eye, increase the curvature radius of the slag eye on the side of the iron mouth, and broaden the area of the slag eye. At the same time, it can also improve the fluctuation of the slag layer and the liquid surface of molten iron, and reduce the splashing of molten iron and slag entrapment phenomenon, thus improving the slag skimming efficiency.

Fluid Flow, Dissolution, and Mixing Phenomena in a Multibottom Tuyere‐Stirred Gas‐Oxygen Refining Furnace

A three‐dimensional mathematical model on fluid flow, ferrochrome dissolution, and mixing phenomena in a nitrogen‐stirred gas‐oxygen refining furnace is established. The multiphase fluid flow is simulated using the standard k–ε model, the volume of fluid (VOF) model, and the Lagrangian discrete phase model. Interfaces between fluids are tracked by the VOF model, and nitrogen bubbles are treated as discrete phase particles. The melt time of ferrochrome particles and the local mixing time are calculated using the user‐defined function. Effects of gas flow rate and bottom tuyere configuration on the fluid flow and the melting and mixing of ferrochrome are investigated. The results show that the average turbulent kinetic energy and its dissipation rate first increase and then decrease with the increasing gas flow rate, while the melting time and mixing time first decrease and then increase. The shortest melting and mixing time with the condition of seven bottom tuyeres are reached when the gas flow rate is 6.5 Nm3 min−1, which are 40.5 and 94.6 s, respectively. The mixing time decreases from 190.0 to 104.5 s when the three bottom tuyeres configuration changes to the seven bottom tuyeres configuration with the gas flow rate of 3.9 Nm3 min−1.

A Numerical Investigation of the Dynamic Interaction between the Deep-Sea Mining Vehicle and Sediment Plumes Based on a Small-Scale Analysis

The discharge of sediment plumes, which occurs mainly in the two depth zones, has a critical impact on assessing the deep-sea environment. Therefore, it is necessary to establish the corresponding physical oceanography for the evolution of these sediment plumes. For a more accurate evolution estimation of the plumes, the model in this research is concerned with the dynamic interaction between the deep-sea mining vehicle (DSMV) and the sediment plumes on small scales (t ≤ 2 s), contributing to a focus on the vital physical mechanics of controlling the extent of these plumes. The sediment concentration and particle trajectories of the plume emissions were determined using the Lagrangian discrete phase model (DPM). The results show that (1) the wake structure of the DSMV wraps the plume vortex discharged from the rear of the vehicle and inhibits the lateral diffusion of the plume, (2) the length of the entire wake (Lw) increases exponentially as the relative discharge velocity of the plume (U*) increases, where U* is defined as the dimensionless difference between the traveling velocity of the DSMV and the discharge velocity of the plume, and (3) at the same traveling speed of the DSMV and U* less than 0.75, the dispersion of the sediment particles in the early discharge stage of the plume does not vary with the plume discharge rate. This will be beneficial for the more accurate monitoring of ecological changes in deep-sea mining activities and provide theoretical guidance for the green design of DSMVs.

Computational fluid dynamics and experimental validation of aerosol jet printing with multi-stage flow focusing lenses

A 3D computational fluid dynamics (CFD) framework is presented to model and explain critical aerodynamic interactions occurring in the printhead during aerosol jet printing (AJP) with multi-stage flow focusing lenses. AJP has demonstrated great potential to fabricate complex circuits and conductive devices for numerous applications, including flexible electronics, medical diagnostic devices, and fuel cells. However, the devices manufactured by AJP are currently relegated to prototype roles due to poor repeatability of the deposited structures. The lack of process consistency in AJP arises from an incomplete understanding of causal aerodynamic interactions that influence the structure and repeatability of the printed features. Herein, a comprehensive CFD framework is presented to analyze the effects of gas flow rates, nozzle geometry, stand-off distance, printhead design, and aerosol droplet size on the resolution and morphology of printed features. Compressible Navier-Stokes equations with a k-ε turbulence model are solved to simulate flow conditions in the aerosol jet printhead. Additionally, a Lagrangian discrete phase model is used to simulate the transport of aerosolized ink droplets through the turbulent shear flow. The results highlight the crucial role of the design of the mist tube and the first aerodynamic lens, the density of the sheath gas, and the size of the droplets in the aerosol stream in determining print resolution and quality. A favorable comparison was found between numerically calculated results and experimental data obtained using the NanoJet™ system. CFD models presented in this work are expected to aid in identifying optimal process windows a priori, to improve process consistency.

Effect of Mold Electromagnetic Stirring on Metallurgical Behavior in Ultrahigh Speed Continuous Casting Billet Mold

A three‐dimensional model of fluid flow, heat transfer, solidification, and inclusion motion in billet mold at ultrahigh casting speed under electromagnetic field is developed. The low Reynolds number k–ε model coupled with electromagnetic model and Lagrangian discrete phase model is used to investigate the flow field, temperature field, solidification, and inclusions transport under different current intensities. The results show that mold electromagnetic stirring (M‐EMS) significantly alters the flow pattern of molten steel. The impact depth of the molten steel decreases as the stirring current intensity increases, and the horizontal swirl intensities of the molten steel increase with the stirring current intensity. As the current intensity increases from 500 to 700 A, the impact depth decreases from 0.637 to 0.575 m and the maximum tangential velocity increases from 0.477 to 0.898 m s−1. When the stirring current is intense, the flow of molten steel near the mold exit is reversed, and the molten steel flows asymmetrically and unsteadily. The M‐EMS effectively improves the transverse heat transfer of the molten steel in the mold, contributing to the dissipation of the molten steel superheat and the growth of the solidified shell. In addition, the removal ratio of the inclusions is improved significantly.

Effect of transient breathing cycle on the deposition of micro and nanoparticles on respiratory walls

Background and objectiveFrom various perspectives (e.g. inhalation exposure and drug delivery), it is important to provide insights into the behavior of inhaled particles in the human respiratory system. Although most of the experimental and numerical studies have relied on an assumption of steady inhalation, the transient breathing profile is a key factor in particle deposition in the respiratory tract. In this study, particle transportation and deposition were predicted in a realistic human airway model during a breathing cycle and the effects of steady-state and transient flows on the deposition fraction were observed using computational fluid dynamics. MethodsTwo transient breathing cycles with different respiratory durations were considered to evaluate the effects of respiration duration on particle transport and deposition characteristics. Two types of steady breathing conditions with corresponding steady-state respiratory volumes were reproduced. The Lagrangian discrete phase model approach was used to investigate particle transportation and deposition under transient breathing conditions. Additionally, the Eulerian approach was used to analyze the transport of nanoparticles in the gas phase. A total of >50,000 monodispersed particles with aerodynamic diameters ranging between 2 nm and 10 μm were selected for comprehensive deposition predictions for particle sizes ranging from the nano- to microscale. ResultsThe predicted results were compared with the experimental data. The particle deposition fraction in the nasal cavity and tracheal regions showed differences between the steady and transient simulations. In addition, particle analysis under steady inhalation conditions cannot accurately predict particle transportation and deposition in the lower airway. Furthermore, the breathing cycle had a significant effect on the deposition fraction of the particles and the behavior of the inhaled particles. ConclusionsTransient simulation mimicking the breathing cycle was observed to be an important factor in accurately predicting the transportation and deposition of particles in the respiratory tract.

Influence of the ventilation strategy on the respiratory droplets dispersion inside a coach bus: CFD approach

The airborne transmission of the COVID-19 virus was considered the main cause of infection. The increasing concern about the virus spread in confined spaces, characterized by high crowding indexes and an often-inadequate air exchange system, pushes the scientific community to the design of many studies aimed at improving indoor air quality. The risk of transmission depends on several factors such as droplet properties, virus characteristics, and indoor airflow patterns. The main transmission route of the SARS-CoV-2 virus to humans is the respiratory route through small (<100 μm) and large droplets. In an indoor environment, the air exchange plays a fundamental role on the dispersion of the droplets. In this study, an integrated approach was developed to evaluate the influence of the ventilation strategy on the dispersion of respiratory droplets emitted inside a coach bus. There are no specific guidelines and standards on the air exchange rate (AER) values to be respected in indoor environments such as coach buses. The aim of this work is to analyse the influence of ventilation strategy on the respiratory droplet concentration and distribution emitted in a coach bus. Ansys FLUENT was used to numerically solve the well-known transient Navier-Stokes equations (URANS equations), the energy equation and using the Lagrangian Discrete Phase Model (DPM) approach to construct the droplet trajectories. The geometry is representative of an intercity bus, a vehicle constructed exclusively for the carriage of seated passengers. The 3D CAD model represented a coach bus with an HVAC system, within which an infected subject was present. The positions of exhaust vents and air-conditioning vents were chosen to ensure complete air circulation throughout the bus. The infected subject emitted droplets with a well-defined size distribution and mass through the mouth. The air exchange is provided in two different ways: general ventilation (from air intakes positioned along the bus windows and top side of central corridor) and personal ventilation (with air intakes for each passenger). For the general ventilation a single AER value was set (0.3 m3 s−1). The first results obtained showed a slight particle dispersion in the computational domain due to the airflow rate entered through the HVAC system, but a still elevated level of particle concentration tended to accumulate on the area near to infected subject. Additional analysis was executed to evaluate the beneficial effects linked to further addition of airflow through personal air-conditioning vents placed above every passenger’s head. The results show the importance of the use of the ventilation system inside a coach bus, highlighting how the contribution linked to of the personal air exchange rate can lead to a significant reduction of droplet concentration exposure and consequently a reduction of the risk of infection from airborne diseases.

Numerical and experimental investigation of aerosol jet printing

A two-dimensional computational fluid dynamics model is presented to elucidate the fundamental aerodynamic phenomena dictating the morphology of aerosol jet printed features. Under compressible and laminar flow assumptions, governing equations were numerically solved to calculate crucial flow variables at discrete points throughout the fluid domain. Randomized single-factor numerical experiments were performed to unravel the role of volumetric flow rates of sheath gas, carrier gas, flow focusing ratio, overall gas flow rate, and aerosol droplet diameter. A Lagrangian discrete phase model was implemented to predict the trajectories of aerosol streams through the fluid domain at several process conditions. A mathematical model for predicting the width of the aerosol stream at the nozzle exit is also presented. Additionally, polydispersity in the droplet diameter distribution was modeled using the Rosin-Rammler distribution, and the role of the minimum droplet diameter in a polydisperse stream of aerosols in causing overspray is discussed. Overall, the numerical results showed good agreement with experimental measurements from an ultrasonic aerosol jet printing (AJP) system, making the computational framework a valuable tool for optimizing the printing process and for predicting the occurrence of printing defects.

Turbulence models and simulation method in the CFD simulation of 75-mm hydrocyclone

In this paper, an effective method for the classification process simulation in 75¬mm hydrocyclone is considered. The simulation results and computational time are compared using Reynolds stress model (RSM) and different large eddy simulation (LES) subgrid-scale models as turbulence models, and the volume of fluid model (VOF) as a multiphase model. The Lagrangian discrete phase model (DPM) is used to simulate the classification process of particles. As the experimental result for comparison of simulation results, Hsieh's experimental data are used. When the different LES subgrid-scale models are used, the solution converges stably by various solution convergence methods without increasing the grid numbers or reducing the size of time steps than RSM model. As a result, it is confirmed that when an appropriate simulation method is applied with the LES-WMLES S-Omega model, more accurate axial water flow velocity distribution and particle classification simulation results can be obtained at a computational cost similar to that of using the RSM model.

Experiment and numerical investigation of inhalable particles and indoor environment with ventilation system

After the outbreak of COVID-19, the indoor environment has become particularly important in closed spaces, being a common concern in environmental science and public health, and of great significance for the building environment. To improve the indoor air quality and control the spread of viruses, the analysis of inhalable particles in indoor environments is critical. In this research, we study standards focused on inhalable particles and indoor environmental quality, as well as analyzing the movement and diffusion of indoor particles. Based on our analysis, we conduct an experimental study to determine the distribution of indoor inhalable particles of different sizes before and after diffusion under the conditions of underfloor air distribution. Furthermore, the mathematical modeling method is adopted to simulate the indoor flow field, particle trajectories, and pollutant dispersion process. The k-ε two-equation model is applied as the turbulence model in the numerical simulation, while the Lagrangian discrete phase model is adopted to trace the motion of particles and analyze the distribution characteristics of indoor particles. The results demonstrate that fine particles (i.e., those with size less than 0.5 μm) have a significant impact on the indoor particle concentration, while coarse particles (i.e., with size above 2.5 μm) have a greater influence on the total mass concentration of indoor particles. Small-sized particles can easily follow the airflow and diffuse to upper parts of the room. Overall, the effects of indoor particles on indoor air quality, including the potential threat of aerosol transmission of respiratory infectious diseases, are non-negligible. Application of the presented research can contribute to improving the health-related aspects of the building environment.

Assessment of Finite-Rate Chemistry Effects in a Turbulent Dilute Ethanol Spray Flame

Simulations of a benchmark ethanol dilute spray flame are performed with four combustion models at different levels of closure for turbulence–chemistry interaction (TCI) to provide a head-to-head comparative analysis on the closure effects of TCI. The evaluation is performed in the context of Reynolds-averaged Navier–Stokes simulations taking advantage of the simple jet configuration, together with a Lagrangian discrete phase model for tracking the spray droplets. Two well-validated ethanol mechanisms consisting of 40 and 50 species, respectively, are employed to describe the chemical kinetics and reveal the impact of chemistry. Results are compared against measurement, including gas-phase velocity, temperature, and droplet velocity, demonstrating the improvement with the increasing accuracy in TCI modeling from characteristic time scale model, laminar finite rate model, eddy dissipation concept model, and transported probability density function (PDF) model. Effects of micromixing in PDF simulation are further investigated considering different model formulations and mechanical-to-scalar timescale ratios (). The Euclidean minimum spanning tree model with yields the best prediction of the mean temperature. The analysis on flame structure suggests that the flame exhibits a mixed mode of combustion, i.e., a stratified premixed flame in the upstream and a typical non-premixed flame in the downstream.

High pressure direct injection of gaseous fuels using a discrete phase methodology for engine simulations

Direct gaseous fuel injection in internal combustion engines is a potential strategy for improving in-cylinder combustion processes, performance and emissions outputs and, in the case of hydrogen, could facilitate a transition away from fossil fuel usage. Computational fluid dynamic studies are required to fully understand and optimise the combustion process, however, the fine grids required to adequately model the underexpanded gas jets which tend to result from direct injection make this a difficult and cumbersome task. In this paper the gaseous sphere injection (GSI) model, which utilises the Lagrangian discrete phase model to represent the injected gas jet, is further improved to account for the variation in the jet core length with better estimation due to total pressure ratio change. The improved GSI model is then validated against experimental hydrogen and methane underexpanded freestream jet studies, mixing in a direct injection hydrogen spark ignition engine and combustion in a pilot ignited direct injection methane compression ignition engine. The improved GSI model performs reasonably well across all cases examined which cover various pressure ratios, injector diameters, injection conditions and disparate gases (hydrogen and methane) while also allowing for relatively coarse meshes (cheaper computational cost) to be used when compared to those needed for fully resolved modelling of the gaseous injection process. The improved GSI model should allow for efficient and accurate investigation of direct injection gaseous fuelled engines.

Influence of the Visitor Walking on Airflow and the Bioaerosol Particles in Typical Open Tomb Chambers: An Experimental and Case Study

Effective maintenance of ancient buildings is paid more and more attention worldwide. Many ancient buildings with high inheritance value were gradually destroyed, especially for murals in the open tombs. The bioaerosol particles (BPs) are the major source of contamination in murals and visitor walking could increase this hazard. In order to study the impact of visitors walking on the air flow and the distribution of BPs in the typical tomb chambers, the k-ε and Lagrangian discrete phase model were adopted. The walking visitor was described by the dynamic mesh, and the concentration of BPs in the simulation was verified by experimental sampling. The distribution and migration mechanism of contamination in the chamber were dynamically analyzed. The results indicate that the denser vortex generated when a visitor was walking, and the concentration of BPs changed obviously. Therefore, the number of BPs deposited on some precious murals increased and the contamination location shifted in the direction of visitor walking. In addition, the deposition time of BPs was lagging which would cause potential risk. This research can provide scientific basis for reducing murals contamination during visitor visiting and a reference for the maintenance of ancient buildings.

The dynamics of reinforced particle migration in laser powder bed fusion of Ni-based composite

The dynamics of the reinforced particles' migration remains unclear during the rapid non-equilibrium laser powder bed fusion (LPBF) process. Conducting real-time observations to obtain a comprehensive understanding of the reinforcements' movement is challenging due to the complex physical phenomena that occur during experimentation. The proposed numerical simulation in the present study incorporates a Lagrangian discrete phase model (DPM) to simulate the added submicrometre-sized TiC particles. The simulation results indicate that the migration of TiC particles was primarily induced by the combination of recoil pressure and Marangoni convection force. The TiC particles were also noted to be relatively uniformly distributed in the LPBF-fabricated Hastelloy X-1 wt% TiC composite under a 600 mm/s scanning speed. The present study offers insights into understanding the dynamics of added reinforced phases within the LPBF additive-manufacturing process to further accelerate the development of advanced metal matrix composites processed using the LPBF process.

COVID-19 and urban spaces: A new integrated CFD approach for public health opportunities

Safe urban public spaces are vital owing to their impacts on public health, especially during pandemics such as the ongoing COVID-19 pandemic. Urban public spaces and urbanscape elements must be designed with the risk of viral transmission in mind. This work therefore examines how the design of urbanscape elements can be revisited to control COVID-19 transmission dynamics. Nine proposed models of urban public seating were thus presented and assessed using a transient three-dimensional computational fluid dynamics (CFD) model, with the Eulerian–Lagrangian method and discrete phase model (DPM). The proposed seating models were evaluated by their impact on the normalized air velocity, the diameter of coughing droplets, and deposition fraction. Each of the proposed models demonstrated an increase in the normalized velocity, and a decrease in the deposition fraction by >29%. Diagonal cross linear and curved triangle configurations demonstrated an improved airflow momentum and turbulent flow, which decreased the droplets deposition fraction by 68%, thus providing an improved, healthier urban public seating option.